Polinsky Lab Meeting:
Ewan Dunbar (Laboratoire de Sciences Cognitives et Psycholinguistique, ENS / EHESS / CNRS)
Context in phonological development: Computational approaches
Wednesday, February 12 | 5:30pm | 2 Arrow Street (4th floor conference room)
Early cognitive development in the systems implied in perceiving and producing speech (phonological processing) is well-studied experimentally and observationally. Recently, statistical machine learning tools have begun to address three fundamental problems in phonological development: perceptual learning, morpheme segmentation, and lexical organization. In this talk, I address an issue that cross-cuts all three problems: contextual adaptation. I focus primarily on the perceptual learning problem. Using Bayesian models of category learning, I argue against a widespread assumption in developmental psycholinguistics, in which early speech perceptual development largely consists of the formation of context-independent segmental categories, while sensitivity to coarticulatory and allophonic effects of speech context must wait for a later stage of more abstract development. I propose a new model, in which phonetic units are inherently context-dependent. The model is analogous to standard approaches to talker normalization in speech recognition, has support from the cross-linguistic typology of allophony and coarticulation, and is grossly consistent with the behavioral evidence about the role of phonetic context in speech perception. I also briefly discuss an approach to lexicon organization and word segmentation in which the ideal learner is characterized as adhering to a measure of overall lexicon "coherence", by which top-down effects of semantic context can influence phonological development. Finally, I outline the very recent emergence of collaboration and methodological convergence between developmental psycholinguistic modeling and unsupervised or low-resource automatic speech recognition (ASR) research, where models must be trained without any phoneme labels. This engineering problem corresponds perfectly to the learning problem the infant faces. I argue that, in ASR, too, handling contextual variability is a sine qua non, but that standard approaches are difficult or impossible to recreate in the unsupervised setting; effective methods for contextual adaptation in the unsupervised setting are thus a defining issue for the coming decades of ASR research. I suggest a few ways in which domain knowledge from speech sciences may be able to help us build better models both for ASR and for answering developmental questions.
MIT Colloquium 
Elena Anagnostopoulou (University of Crete)
Decomposing adjectival/ stative passives
Friday, February 14 | 3:30-5pm | 32-141
SCLA Conference
The 13th Annual Conference of the Slavic Cognitive Linguistics Association (SCLC-2014) will take place February 15-17, 2014. The conference is organized by the Department of Slavic Languages and Literatures, the Provostial Fund Committee for the Arts and Humanities, the Department of Linguistics, the Davis Center for Russian and Eurasian Studies, and the Language Resource Center at Harvard University. The program for the conference can be found here.